code: def classification_model_functional():
      input_layer = Input(shape=(784,))
      hidden = Dense(128, activation="relu")(input_layer)
      dropout = Dropout(0.2)(hidden)
      hidden2 = Dense(128, activation="relu")(dropout)
      dropout2 = Dropout(0.2)(hidden2)
      output = Dense(10, activation="softmax")(dropout2)
      model = Model(inputs=input_layer, outputs=output)
      return model
  
file_path: elephas/tests/conftest.py
imports: import pytest
  from tensorflow.keras import Sequential, Input, Model
  from tensorflow.keras.datasets import mnist, boston_housing
  from tensorflow.keras.layers import Dense, Activation, Dropout
  from tensorflow.keras.utils import to_categorical
label_desc: Use image node_id 3 for calling a global function with example usage: classification_model_functional() and returns: model